Detecting microarray data supported microRNA-mRNA interactions

被引：5

作者：

Liu, Hui ^{[1
,3
]}

Zhou, Shuigeng ^{[1
,2
]}

Guan, Jihong ^{[4
]}

机构：

[1] Fudan Univ, Sch Comp Sci, Shanghai 200433, Peoples R China

[2] Fudan Univ, Shanghai Key Lab Intelligent Informat Proc, Shanghai 200433, Peoples R China

[3] Jiangsu Polytech Inst, Sch Informat Sci & Engn, Jiangsu, Peoples R China

[4] Tongji Univ, Dept Comp Sci & Technol, Shanghai 200092, Peoples R China

来源：

INTERNATIONAL JOURNAL OF DATA MINING AND BIOINFORMATICS | 2010年 / 4卷 / 06期

基金：

中国国家自然科学基金;

关键词：

microRNA; target gene; bipartite graph; microarray; GENE-EXPRESSION; TARGET PREDICTION; ELEGANS; IDENTIFICATION; GENOMICS; SEQUENCE; FEEDBACK;

D O I：

10.1504/IJDMB.2010.037545

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

MicroRNAs (miRNAs) have been recently emerged as a novel class of endogenous post-transcriptional regulators in a variety of animal and plant species. Identifying bona fide miRNA-mRNA interactions is an important but challenging task for our insight into the regulatory mechanism of miRNAs. In this paper, we employ a variant of affinity propagation algorithm customised for bipartite graph to reveal the miRNA-mRNA interactions supported by microarray data. Our extensive experiments on human data sets show that our method performs effectively in screening the miRNA-mRNA interactions predicted by sequence-based approaches to reduce the number of candidate miRNA targets using microarray data.

引用

页码：639 / 655

页数：17

共 36 条

[21] microRNA target predictions in animals [J].

Rajewsky, Nikolaus .

NATURE GENETICS, 2006, 38 (Suppl 6) :S8-S13

[22] Multiclass cancer diagnosis using tumor gene expression signatures [J].

Ramaswamy, S ;

Tamayo, P ;

Rifkin, R ;

Mukherjee, S ;

Yeang, CH ;

Angelo, M ;

Ladd, C ;

Reich, M ;

Latulippe, E ;

Mesirov, JP ;

Poggio, T ;

Gerald, W ;

Loda, M ;

Lander, ES ;

Golub, TR .

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2001, 98 (26) :15149-15154

[23] Fast and effective prediction of microRNA/target duplexes [J].

Rehmsmeier, M ;

Steffen, P ;

Höchsmann, M ;

Giegerich, R .

RNA, 2004, 10 (10) :1507-1517

[24] Gene regulation at the single-cell level [J].

Rosenfeld, N ;

Young, JW ;

Alon, U ;

Swain, PS ;

Elowitz, MB .

SCIENCE, 2005, 307 (5717) :1962-1965

[25] TarBase: A comprehensive database of experimentally supported animal microRNA targets [J].

Sethupathy, P ;

Corda, B ;

Hatzigeorgiou, AG .

RNA, 2006, 12 (02) :192-197

[26] A guide through present computational approaches for the identification of mammalian microRNA targets [J].

Sethupathy, Praveen ;

Megraw, Molly ;

Hatzigeorgiou, Artemis G. .

NATURE METHODS, 2006, 3 (11) :881-886

[27] Animal microRNAs confer robustness to gene expression and have a significant impact on 3′UTR evolution [J].

Stark, A ;

Brennecke, J ;

Bushati, N ;

Russell, RB ;

Cohen, SM .

CELL, 2005, 123 (06) :1133-1146

[28] Molecular taxonomy of major neuronal classes in the adult mouse forebrain [J].

Sugino, K ;

Hempel, CM ;

Miller, MN ;

Hattox, AM ;

Shapiro, P ;

Wu, CZ ;

Huang, ZJ ;

Nelson, SB .

NATURE NEUROSCIENCE, 2006, 9 (01) :99-107

[29] An E2F/miR-20a autoregulatory feedback loop [J].

Sylvestre, Yannick ;

De Guire, Vincent ;

Querido, Emmanuelle ;

Mukhopadhyay, Utpal K. ;

Bourdeau, Veronique ;

Major, Francois ;

Ferbeyre, Gerardo ;

Chartrand, Pascal .

JOURNAL OF BIOLOGICAL CHEMISTRY, 2007, 282 (04) :2135-2143

[30] Gene regulatory network growth by duplication [J].

Teichmann, SA ;

Babu, MM .

NATURE GENETICS, 2004, 36 (05) :492-496

← 1 2 3 4 →